Is there any interaction of resistin and adiponectin levels with protein‐energy wasting among patients with chronic kidney disease
Bibliographic record
Abstract
The aim of this study was to evaluate the effects of adipocytokines including adiponectin, leptin, resistin, neuropeptide Y and ghrelin in chronic kidney disease (CKD) patients on appearance of protein-energy wasting (PEW). One hundred fifty patients with mean age of 45.4 ± 15.9 years, without active infections or chronic inflammatory conditions were recruited into the study. Study groups were control group (consisting of 30 healthy volunteers with normal kidney functions), hemodialysis group, predialysis group, peritoneal dialysis group and kidney transplant group. Fasting morning serum leptin, ghrelin, acylated ghrelin, neuropeptide Y, adiponectin, resistin levels of all of the groups were measured. Anthropometric and nutritional assessments of all patients were obtained. Diagnosis of PEW was made according to definition recommended by the International Society of Renal Nutrition and Metabolism. Presence of PEW in hemodialysis (23.3%) and peritoneal dialysis (26.7%) groups were significantly higher than those of predialysis (3.3%), and transplantation (0%) groups. Adiponectin and resistin levels in predialysis, peritoneal dialysis and hemodialysis patients were significantly higher than control group (p: 0.0001). This study had given significant positive correlations between presence of PEW and serum resistin (r: 0.267, p: 0.001), and serum adiponectin levels (r: 0.349, p: 0.0001). There were no relationship between presence of PEW and ghrelin, acylated-ghrelin, neuropeptide Y, and leptin levels of the groups. CKD patients except transplant patients had higher adiponectin and resistin levels than control group. PEW was found to be linearly correlated with resistin and adiponectin. High serum resistin and adiponectin levels might have a role in development of PEW among dialysis patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".